{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Developer Salary 程序员工资调查\n",
    "我在4月1日到3日之间，抓取了某招聘网站的软件和互联网类招聘数据40万条，其中通过程序判断为程序员的14万条。地域方面，我选择了24个主要城市。不过本文只以一线城市为研究对象。这样是为了和我2017年6月的数据做对比。\n",
    "\n",
    "提到2017年的文章，现在居然还有很多人，把这篇文章拿出来炒作。对于社会来说，可气的是，他们直接把2017改成2019，就发表了，这不是骗人么？！对于我来说，可气的是，他们转载居然还冒充是原创，是可忍熟不可忍！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sys\n",
    "sys.path.append('..')\n",
    "sys.path.append('../py')\n",
    "import db\n",
    "import inspect\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus']=False #用来正常显示负号\n",
    "import seaborn as sns\n",
    "import scipy.stats as stats\n",
    "import numpy as np\n",
    "import weighted\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn=db.get_conn()\n",
    "data_original=pd.read_sql(sql=\"select * from _201903v2 where monthly_salary>0 and monthly_salary<80000 and YEAR(publish_date)=2019 and MONTH(publish_date)=3\", con=conn)\n",
    "conn.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "error_job_ids=['104660258','104142922','108434795','101357291','106253516','110368302','111391233','108665401','109277048'\n",
    "                  ,'73857191','108584955','102824950','102824949','111391233','110884556']\n",
    "data=data_original[~data_original.job_id.isin(error_job_ids)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#del data['publish_date']\n",
    "#del data['published_on_weekend']\n",
    "#del data['title']\n",
    "#del data['title']\n",
    "#del data['company_title']\n",
    "#del data['company_description']\n",
    "#del data['job_description']\n",
    "#del data['job_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>job_id</th>\n",
       "      <th>monthly_salary</th>\n",
       "      <th>headcount</th>\n",
       "      <th>title</th>\n",
       "      <th>career</th>\n",
       "      <th>city</th>\n",
       "      <th>company_description</th>\n",
       "      <th>company_size</th>\n",
       "      <th>company_title</th>\n",
       "      <th>company_type</th>\n",
       "      <th>...</th>\n",
       "      <th>pl_visual_basic</th>\n",
       "      <th>publish_date</th>\n",
       "      <th>published_on_weekend</th>\n",
       "      <th>tag_baby_care</th>\n",
       "      <th>tag_five_insurance</th>\n",
       "      <th>tag_flexible</th>\n",
       "      <th>tag_no_overtime</th>\n",
       "      <th>tag_rest_one_day</th>\n",
       "      <th>tag_rest_two_days</th>\n",
       "      <th>tag_stock</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19021</th>\n",
       "      <td>109606295</td>\n",
       "      <td>7000.0</td>\n",
       "      <td>450</td>\n",
       "      <td>网游公司招聘（游戏推广、维护、设计）</td>\n",
       "      <td>一般程序员</td>\n",
       "      <td>guangzhou</td>\n",
       "      <td>广州川山教育是集远程高等学历教育、职业化教育、各类培训考证于一体的综合性教育机构。自成立以来...</td>\n",
       "      <td>50-</td>\n",
       "      <td>广州川山教育科技有限公司</td>\n",
       "      <td>民营公司</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>2019-03-13</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27335</th>\n",
       "      <td>110969579</td>\n",
       "      <td>12500.0</td>\n",
       "      <td>200</td>\n",
       "      <td>JAVA开发工程师（2019届应届毕业生）</td>\n",
       "      <td>一般程序员</td>\n",
       "      <td>guangzhou</td>\n",
       "      <td>广州汇智通信技术有限公司是专业从事国家特殊通信系统研制工作的大型国有控股混合所有制企业。公司...</td>\n",
       "      <td>1000-5000</td>\n",
       "      <td>广州汇智通信技术有限公司</td>\n",
       "      <td>国企</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>2019-03-31</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38024</th>\n",
       "      <td>75596794</td>\n",
       "      <td>7500.0</td>\n",
       "      <td>200</td>\n",
       "      <td>JAVA 工程师</td>\n",
       "      <td>一般程序员</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>四方精创资讯有限公司（简称四方精创），是从事金融行业it综合服务和软件协同服务的高端应用软件...</td>\n",
       "      <td>500-1000人</td>\n",
       "      <td>深圳四方精创资讯股份有限公司</td>\n",
       "      <td>合资</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>2019-03-26</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42889</th>\n",
       "      <td>93944455</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>180</td>\n",
       "      <td>2018届毕业生（计算机、软件）</td>\n",
       "      <td>一般程序员</td>\n",
       "      <td>nanjing</td>\n",
       "      <td>江苏海隆是由中国知名的服务外包企业海隆软件投资成立的，海隆软件总部设于上海，注册资金3亿元，...</td>\n",
       "      <td>1000-5000</td>\n",
       "      <td>江苏海隆软件技术有限公司</td>\n",
       "      <td>民营公司</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>2019-03-19</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42901</th>\n",
       "      <td>93977548</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>180</td>\n",
       "      <td>储备海外业务软件工程师（2018届应届生）</td>\n",
       "      <td>一般程序员</td>\n",
       "      <td>nanjing</td>\n",
       "      <td>江苏海隆是由中国知名的服务外包企业海隆软件投资成立的，海隆软件总部设于上海，注册资金3亿元，...</td>\n",
       "      <td>1000-5000</td>\n",
       "      <td>江苏海隆软件技术有限公司</td>\n",
       "      <td>民营公司</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>2019-03-19</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 90 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          job_id  monthly_salary  headcount                  title career  \\\n",
       "19021  109606295          7000.0        450     网游公司招聘（游戏推广、维护、设计）  一般程序员   \n",
       "27335  110969579         12500.0        200  JAVA开发工程师（2019届应届毕业生）  一般程序员   \n",
       "38024   75596794          7500.0        200               JAVA 工程师  一般程序员   \n",
       "42889   93944455          5000.0        180       2018届毕业生（计算机、软件）  一般程序员   \n",
       "42901   93977548          5000.0        180  储备海外业务软件工程师（2018届应届生）  一般程序员   \n",
       "\n",
       "            city                                company_description  \\\n",
       "19021  guangzhou  广州川山教育是集远程高等学历教育、职业化教育、各类培训考证于一体的综合性教育机构。自成立以来...   \n",
       "27335  guangzhou  广州汇智通信技术有限公司是专业从事国家特殊通信系统研制工作的大型国有控股混合所有制企业。公司...   \n",
       "38024   shenzhen  四方精创资讯有限公司（简称四方精创），是从事金融行业it综合服务和软件协同服务的高端应用软件...   \n",
       "42889    nanjing  江苏海隆是由中国知名的服务外包企业海隆软件投资成立的，海隆软件总部设于上海，注册资金3亿元，...   \n",
       "42901    nanjing  江苏海隆是由中国知名的服务外包企业海隆软件投资成立的，海隆软件总部设于上海，注册资金3亿元，...   \n",
       "\n",
       "      company_size   company_title company_type    ...      pl_visual_basic  \\\n",
       "19021          50-    广州川山教育科技有限公司         民营公司    ...                False   \n",
       "27335    1000-5000    广州汇智通信技术有限公司           国企    ...                False   \n",
       "38024    500-1000人  深圳四方精创资讯股份有限公司           合资    ...                False   \n",
       "42889    1000-5000    江苏海隆软件技术有限公司         民营公司    ...                False   \n",
       "42901    1000-5000    江苏海隆软件技术有限公司         民营公司    ...                False   \n",
       "\n",
       "       publish_date  published_on_weekend  tag_baby_care  tag_five_insurance  \\\n",
       "19021    2019-03-13                 False          False               False   \n",
       "27335    2019-03-31                  True          False                True   \n",
       "38024    2019-03-26                 False          False                True   \n",
       "42889    2019-03-19                 False          False                True   \n",
       "42901    2019-03-19                 False          False                True   \n",
       "\n",
       "       tag_flexible  tag_no_overtime  tag_rest_one_day  tag_rest_two_days  \\\n",
       "19021         False            False             False              False   \n",
       "27335         False            False             False              False   \n",
       "38024         False            False             False              False   \n",
       "42889          True            False             False              False   \n",
       "42901          True            False             False              False   \n",
       "\n",
       "       tag_stock  \n",
       "19021      False  \n",
       "27335      False  \n",
       "38024      False  \n",
       "42889      False  \n",
       "42901      False  \n",
       "\n",
       "[5 rows x 90 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=data.sort_values(by='headcount', ascending=False)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pd_weighted_mean(group, avg_name, weight_name):\n",
    "    \"\"\" http://stackoverflow.com/questions/10951341/pandas-dataframe-aggregate-function-using-multiple-columns\n",
    "    In rare instance, we may not have weights, so just return the mean. Customize this if your business case\n",
    "    should return otherwise.\n",
    "    \"\"\"\n",
    "    d = group[avg_name]\n",
    "    w = group[weight_name]\n",
    "    try:\n",
    "        return (d * w).sum() / w.sum()\n",
    "    except ZeroDivisionError:\n",
    "        return d.mean()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Unilateral Stats 总体统计"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "有数据可知，程序员向一线城市集中的趋势非常明显。\n",
    "\n",
    "According to the statistics, significant amount of developers are in the first tier cities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 3750.,  9000., 12500., 17500., 33750.])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary_mean=weighted.weighted_mean(data.monthly_salary.values, data.headcount.values)\n",
    "q=weighted.weighted_quantile(data.monthly_salary.values,[0.025,0.25,0.5,0.75,0.975], data.headcount.values)\n",
    "q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019年中国程序员的平均工资为13769元，工资中位数为12500元，其中95%的人的工资位于3750到33750元之间。\n"
     ]
    }
   ],
   "source": [
    "print('2019年中国程序员的平均工资为{:.0f}元，工资中位数为{:.0f}元，其中95%的人的工资位于{:.0f}到{:.0f}元之间。'\n",
    "      .format(salary_mean, q[2], q[0], q[4]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In 2019, Developers in China earn 13769 Yuan as average, the median is 12500 Yuan, 95% of them earn between 3750 and 33750 Yuan.\n"
     ]
    }
   ],
   "source": [
    "print('In 2019, Developers in China earn {:.0f} Yuan as average, '\n",
    "      'the median is {:.0f} Yuan, 95% of them earn between {:.0f} and {:.0f} Yuan.'\n",
    "      .format(salary_mean, q[2], q[0], q[4]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23325328fd0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.monthly_salary.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It does not look like normal distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NormaltestResult(statistic=16697.978628531244, pvalue=0.0)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.normaltest(data.monthly_salary)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "null hypothesis: x comes from a normal distribution\n",
    "    \n",
    "p=0\n",
    "\n",
    "The null hypothesis can be rejected\n",
    "\n",
    "conclusion: data is not normally distributed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Zoom in"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[data.monthly_salary<40000].monthly_salary.hist()\n",
    "plt.annotate('https://github.com/juwikuang/job_survey', xy=(0,0), xytext=(2000, 100), color='white')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Role 角色"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Common Functions\n",
    "def get_sub_stats_by_col(data, col):\n",
    "    categories=data[col].unique()\n",
    "    salary_mean=[]\n",
    "    salary_95_min=[]\n",
    "    salary_95_max=[]\n",
    "    salary_median=[]\n",
    "\n",
    "    count=[]\n",
    "    \n",
    "    categorys_out=[]\n",
    "    for category in categories:\n",
    "        #print(feature)\n",
    "        idata=data[data[col]==category]\n",
    "        headcount=idata.headcount.sum()\n",
    "        values = idata.monthly_salary.values\n",
    "        weights = idata.headcount.values\n",
    "        #print(str(headcount))\n",
    "        if headcount==0:\n",
    "            continue\n",
    "        \n",
    "        salary_mean.append(np.average(values, weights=weights))\n",
    "        \n",
    "\n",
    "        q = weighted.weighted_quantile(values,[0.025,0.5,0.975],weights)\n",
    "        salary_95_min.append(q[0])\n",
    "        salary_median.append(q[1])\n",
    "        salary_95_max.append(q[2])\n",
    "        count.append(idata.headcount.sum())\n",
    "        categorys_out.append(category)\n",
    "    sub_data=pd.DataFrame()\n",
    "    sub_data[col]=[c for c in categorys_out]\n",
    "    sub_data['salary_mean']=salary_mean\n",
    "    sub_data['salary_95_min']=salary_95_min\n",
    "    sub_data['salary_median']=salary_median\n",
    "    sub_data['salary_95_max']=salary_95_max\n",
    "    sub_data['head_count']=count\n",
    "    sub_data['percentage']=count/np.sum(count)\n",
    "    sub_data=sub_data.sort_values(by='salary_mean', ascending=False)\n",
    "\n",
    "    return sub_data\n",
    "\n",
    "def get_sub_stats_by_prefix(data, prefix):\n",
    "    \n",
    "    features = [feature for feature in data.columns if feature.startswith(prefix)]\n",
    "    salary_mean=[]\n",
    "    salary_median=[]\n",
    "    salary_95_min=[]\n",
    "    salary_95_max=[]\n",
    "    count=[]\n",
    "    \n",
    "    features_out=[]\n",
    "    for feature in features:\n",
    "        #print(feature)\n",
    "        idata=data[data[feature]==1]\n",
    "        headcount=idata.headcount.sum()\n",
    "        values = idata.monthly_salary.values\n",
    "        weights = idata.headcount.values\n",
    "        #print(str(headcount))\n",
    "        if headcount==0:\n",
    "            continue\n",
    "        \n",
    "        salary_mean.append(weighted.weighted_mean(values, weights))\n",
    "        q = weighted.weighted_quantile(values,[0.025,0.5,0.975],weights)\n",
    "        salary_median.append(q[1])\n",
    "        salary_95_min.append(q[0])\n",
    "        salary_95_max.append(q[2])\n",
    "        count.append(idata.headcount.sum())\n",
    "        features_out.append(feature)\n",
    "    sub_data=pd.DataFrame()\n",
    "    sub_data['rank']=range(0,len(features_out))\n",
    "    sub_data[prefix]=[f.replace(prefix,'') for f in features_out]\n",
    "    sub_data['salary_mean']=salary_mean\n",
    "    sub_data['salary_median']=salary_median\n",
    "    sub_data['salary_95_min']=salary_95_min\n",
    "    sub_data['salary_95_max']=salary_95_max\n",
    "    sub_data['head_count']=count\n",
    "    sub_data['percentage']=count/np.sum(count)\n",
    "    sub_data=sub_data.sort_values(by='salary_mean', ascending=False)\n",
    "    sub_data['rank']=range(1,len(features_out)+1)\n",
    "    #sub_data=sub_data.reset_index()\n",
    "    return sub_data\n",
    "\n",
    "def apply_style(sub_data):\n",
    "    return sub_data.style.hide_index().format(\n",
    "        {\"percentage\":\"{:.2%}\",\"salary_mean\":\"{:.0f}\",\"salary_median\":\"{:.0f}\",\"salary_95_min\":\"{:.0f}\",\"salary_95_max\":\"{:.0f}\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"col_heading level0 col0\" >career</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_95_min</th> \n",
       "        <th class=\"col_heading level0 col3\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col4\" >salary_95_max</th> \n",
       "        <th class=\"col_heading level0 col5\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col6\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow0_col0\" class=\"data row0 col0\" >算法工程师</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow0_col1\" class=\"data row0 col1\" >20747</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow0_col2\" class=\"data row0 col2\" >5000</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow0_col3\" class=\"data row0 col3\" >17917</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow0_col4\" class=\"data row0 col4\" >58333</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow0_col5\" class=\"data row0 col5\" >13869</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow0_col6\" class=\"data row0 col6\" >8.62%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow1_col0\" class=\"data row1 col0\" >系统架构师</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow1_col1\" class=\"data row1 col1\" >19803</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow1_col2\" class=\"data row1 col2\" >5250</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow1_col3\" class=\"data row1 col3\" >17500</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow1_col4\" class=\"data row1 col4\" >45000</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow1_col5\" class=\"data row1 col5\" >7379</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow1_col6\" class=\"data row1 col6\" >4.59%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow2_col0\" class=\"data row2 col0\" >爬虫工程师</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow2_col1\" class=\"data row2 col1\" >14799</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow2_col2\" class=\"data row2 col2\" >3333</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow2_col3\" class=\"data row2 col3\" >14000</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow2_col4\" class=\"data row2 col4\" >35000</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow2_col5\" class=\"data row2 col5\" >300</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow2_col6\" class=\"data row2 col6\" >0.19%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow3_col0\" class=\"data row3 col0\" >一般程序员</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow3_col1\" class=\"data row3 col1\" >12753</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow3_col2\" class=\"data row3 col2\" >3750</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow3_col3\" class=\"data row3 col3\" >12500</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow3_col4\" class=\"data row3 col4\" >30000</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow3_col5\" class=\"data row3 col5\" >139230</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow3_col6\" class=\"data row3 col6\" >86.57%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow4_col0\" class=\"data row4 col0\" >生物信息工程师</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow4_col1\" class=\"data row4 col1\" >10518</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow4_col2\" class=\"data row4 col2\" >4500</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow4_col3\" class=\"data row4 col3\" >9750</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow4_col4\" class=\"data row4 col4\" >22500</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow4_col5\" class=\"data row4 col5\" >55</td> \n",
       "        <td id=\"T_6d8d8e28_69c3_11e9_9909_701ce71031efrow4_col6\" class=\"data row4 col6\" >0.03%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x23331412400>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_career = get_sub_stats_by_col(data,'career')\n",
    "apply_style(data_career)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13768.992319155064"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(data.monthly_salary * data.headcount) / data.headcount.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "160833"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.headcount.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    46808.000000\n",
       "mean         3.436015\n",
       "std          4.840314\n",
       "min          1.000000\n",
       "25%          1.000000\n",
       "50%          2.000000\n",
       "75%          5.000000\n",
       "max        450.000000\n",
       "Name: headcount, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.headcount.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>job_id</th>\n",
       "      <th>monthly_salary</th>\n",
       "      <th>headcount</th>\n",
       "      <th>title</th>\n",
       "      <th>career</th>\n",
       "      <th>city</th>\n",
       "      <th>company_description</th>\n",
       "      <th>company_size</th>\n",
       "      <th>company_title</th>\n",
       "      <th>company_type</th>\n",
       "      <th>ageism</th>\n",
       "      <th>db_Apache_Hive</th>\n",
       "      <th>db_CouchBase</th>\n",
       "      <th>db_CouchDB</th>\n",
       "      <th>db_DB2</th>\n",
       "      <th>db_DynamoDB</th>\n",
       "      <th>db_Elasticsearch</th>\n",
       "      <th>db_FileMaker</th>\n",
       "      <th>db_Firebase</th>\n",
       "      <th>db_Firebird</th>\n",
       "      <th>db_Hbase</th>\n",
       "      <th>db_Informix</th>\n",
       "      <th>db_Ingres</th>\n",
       "      <th>db_MariaDB</th>\n",
       "      <th>db_Memcached</th>\n",
       "      <th>db_MongoDB</th>\n",
       "      <th>db_MySQL</th>\n",
       "      <th>db_Neo4j</th>\n",
       "      <th>db_Netezza</th>\n",
       "      <th>db_Oracle</th>\n",
       "      <th>db_PostgreSQL</th>\n",
       "      <th>db_Redis</th>\n",
       "      <th>db_Riak</th>\n",
       "      <th>db_SAP_HANA</th>\n",
       "      <th>db_SQL_Server</th>\n",
       "      <th>db_SQLite</th>\n",
       "      <th>db_Solr</th>\n",
       "      <th>db_Splunk</th>\n",
       "      <th>db_Sybase</th>\n",
       "      <th>db_Teradata</th>\n",
       "      <th>db_dBase</th>\n",
       "      <th>edu</th>\n",
       "      <th>english</th>\n",
       "      <th>experience</th>\n",
       "      <th>expert_adas</th>\n",
       "      <th>expert_blockchain</th>\n",
       "      <th>expert_embed</th>\n",
       "      <th>expert_expert</th>\n",
       "      <th>expert_gis</th>\n",
       "      <th>_996_yes</th>\n",
       "      <th>_996_no</th>\n",
       "      <th>industry</th>\n",
       "      <th>japanese</th>\n",
       "      <th>job_description</th>\n",
       "      <th>job_summary</th>\n",
       "      <th>job_tags</th>\n",
       "      <th>phone_android</th>\n",
       "      <th>phone_app</th>\n",
       "      <th>phone_iso</th>\n",
       "      <th>pl_c_sharp</th>\n",
       "      <th>pl_cpp</th>\n",
       "      <th>pl_delphi</th>\n",
       "      <th>pl_go</th>\n",
       "      <th>pl_haskell</th>\n",
       "      <th>pl_java</th>\n",
       "      <th>pl_javascript</th>\n",
       "      <th>pl_julia</th>\n",
       "      <th>pl_kotlin</th>\n",
       "      <th>pl_lua</th>\n",
       "      <th>pl_matlab</th>\n",
       "      <th>pl_objective_c</th>\n",
       "      <th>pl_perl</th>\n",
       "      <th>pl_php</th>\n",
       "      <th>pl_python</th>\n",
       "      <th>pl_ruby</th>\n",
       "      <th>pl_rust</th>\n",
       "      <th>pl_scrala</th>\n",
       "      <th>pl_swift</th>\n",
       "      <th>pl_typescript</th>\n",
       "      <th>pl_vba</th>\n",
       "      <th>pl_visual_basic</th>\n",
       "      <th>publish_date</th>\n",
       "      <th>published_on_weekend</th>\n",
       "      <th>tag_baby_care</th>\n",
       "      <th>tag_five_insurance</th>\n",
       "      <th>tag_flexible</th>\n",
       "      <th>tag_no_overtime</th>\n",
       "      <th>tag_rest_one_day</th>\n",
       "      <th>tag_rest_two_days</th>\n",
       "      <th>tag_stock</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19021</th>\n",
       "      <td>109606295</td>\n",
       "      <td>7000.0</td>\n",
       "      <td>450</td>\n",
       "      <td>网游公司招聘（游戏推广、维护、设计）</td>\n",
       "      <td>一般程序员</td>\n",
       "      <td>guangzhou</td>\n",
       "      <td>广州川山教育是集远程高等学历教育、职业化教育、各类培训考证于一体的综合性教育机构。自成立以来...</td>\n",
       "      <td>50-</td>\n",
       "      <td>广州川山教育科技有限公司</td>\n",
       "      <td>民营公司</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>大专</td>\n",
       "      <td>False</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>edu</td>\n",
       "      <td>False</td>\n",
       "      <td>月薪3500-8000底薪+补助+社保、五险一金、部分双休。部门免费包住，2.工作地点：可申...</td>\n",
       "      <td>广州-天河区|无工作经验|大专|招450人|03-13发布</td>\n",
       "      <td>绩效奖金,全勤奖,专业培训,节日福利</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2019-03-13</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27335</th>\n",
       "      <td>110969579</td>\n",
       "      <td>12500.0</td>\n",
       "      <td>200</td>\n",
       "      <td>JAVA开发工程师（2019届应届毕业生）</td>\n",
       "      <td>一般程序员</td>\n",
       "      <td>guangzhou</td>\n",
       "      <td>广州汇智通信技术有限公司是专业从事国家特殊通信系统研制工作的大型国有控股混合所有制企业。公司...</td>\n",
       "      <td>1000-5000</td>\n",
       "      <td>广州汇智通信技术有限公司</td>\n",
       "      <td>国企</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>本科</td>\n",
       "      <td>False</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>computer</td>\n",
       "      <td>False</td>\n",
       "      <td>广州汇智通信技术有限公司                                  ...</td>\n",
       "      <td>广州|无工作经验|本科|招200人|03-31发布</td>\n",
       "      <td>五险一金,补充医疗保险,补充公积金,交通补贴,年终奖金,绩效奖金,通讯补贴,定期体检,餐饮补贴</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2019-03-31</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38024</th>\n",
       "      <td>75596794</td>\n",
       "      <td>7500.0</td>\n",
       "      <td>200</td>\n",
       "      <td>JAVA 工程师</td>\n",
       "      <td>一般程序员</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>四方精创资讯有限公司（简称四方精创），是从事金融行业it综合服务和软件协同服务的高端应用软件...</td>\n",
       "      <td>500-1000人</td>\n",
       "      <td>深圳四方精创资讯股份有限公司</td>\n",
       "      <td>合资</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>本科</td>\n",
       "      <td>False</td>\n",
       "      <td>1_3</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>computer</td>\n",
       "      <td>False</td>\n",
       "      <td>岗位职责1.按照上级计划和安排进行技术开发工作；2. 负责金融行业应用平台后端模块开发工作；...</td>\n",
       "      <td>深圳|1年经验|本科|招200人|03-26发布</td>\n",
       "      <td>五险一金,专业培训,年终奖金,员工旅游</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2019-03-26</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42889</th>\n",
       "      <td>93944455</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>180</td>\n",
       "      <td>2018届毕业生（计算机、软件）</td>\n",
       "      <td>一般程序员</td>\n",
       "      <td>nanjing</td>\n",
       "      <td>江苏海隆是由中国知名的服务外包企业海隆软件投资成立的，海隆软件总部设于上海，注册资金3亿元，...</td>\n",
       "      <td>1000-5000</td>\n",
       "      <td>江苏海隆软件技术有限公司</td>\n",
       "      <td>民营公司</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>本科</td>\n",
       "      <td>True</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>computer</td>\n",
       "      <td>True</td>\n",
       "      <td>职位描述：1. 从事对日大型应用软件（证券、保险、银行、交通等）系统的详细设计、开发和测试等...</td>\n",
       "      <td>南京-鼓楼区|无工作经验|本科|招180人|03-19发布|英语良好|计算机科学与技术计算机网络</td>\n",
       "      <td>五险一金,员工旅游,交通补贴,餐饮补贴,专业培训,出国机会,绩效奖金,年终奖金,弹性工作,定期体检</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2019-03-19</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42901</th>\n",
       "      <td>93977548</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>180</td>\n",
       "      <td>储备海外业务软件工程师（2018届应届生）</td>\n",
       "      <td>一般程序员</td>\n",
       "      <td>nanjing</td>\n",
       "      <td>江苏海隆是由中国知名的服务外包企业海隆软件投资成立的，海隆软件总部设于上海，注册资金3亿元，...</td>\n",
       "      <td>1000-5000</td>\n",
       "      <td>江苏海隆软件技术有限公司</td>\n",
       "      <td>民营公司</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>本科</td>\n",
       "      <td>False</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>computer</td>\n",
       "      <td>True</td>\n",
       "      <td>职位描述：1. 从事对日大型应用软件（证券、保险、银行、交通等）系统的详细设计、开发和测试等...</td>\n",
       "      <td>南京-鼓楼区|无工作经验|本科|招180人|03-19发布</td>\n",
       "      <td>五险一金,员工旅游,交通补贴,餐饮补贴,专业培训,出国机会,绩效奖金,年终奖金,弹性工作,定期体检</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2019-03-19</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          job_id  monthly_salary  headcount                  title career  \\\n",
       "19021  109606295          7000.0        450     网游公司招聘（游戏推广、维护、设计）  一般程序员   \n",
       "27335  110969579         12500.0        200  JAVA开发工程师（2019届应届毕业生）  一般程序员   \n",
       "38024   75596794          7500.0        200               JAVA 工程师  一般程序员   \n",
       "42889   93944455          5000.0        180       2018届毕业生（计算机、软件）  一般程序员   \n",
       "42901   93977548          5000.0        180  储备海外业务软件工程师（2018届应届生）  一般程序员   \n",
       "\n",
       "            city                                company_description  \\\n",
       "19021  guangzhou  广州川山教育是集远程高等学历教育、职业化教育、各类培训考证于一体的综合性教育机构。自成立以来...   \n",
       "27335  guangzhou  广州汇智通信技术有限公司是专业从事国家特殊通信系统研制工作的大型国有控股混合所有制企业。公司...   \n",
       "38024   shenzhen  四方精创资讯有限公司（简称四方精创），是从事金融行业it综合服务和软件协同服务的高端应用软件...   \n",
       "42889    nanjing  江苏海隆是由中国知名的服务外包企业海隆软件投资成立的，海隆软件总部设于上海，注册资金3亿元，...   \n",
       "42901    nanjing  江苏海隆是由中国知名的服务外包企业海隆软件投资成立的，海隆软件总部设于上海，注册资金3亿元，...   \n",
       "\n",
       "      company_size   company_title company_type  ageism  db_Apache_Hive  \\\n",
       "19021          50-    广州川山教育科技有限公司         民营公司    True           False   \n",
       "27335    1000-5000    广州汇智通信技术有限公司           国企   False           False   \n",
       "38024    500-1000人  深圳四方精创资讯股份有限公司           合资   False           False   \n",
       "42889    1000-5000    江苏海隆软件技术有限公司         民营公司   False           False   \n",
       "42901    1000-5000    江苏海隆软件技术有限公司         民营公司   False           False   \n",
       "\n",
       "       db_CouchBase  db_CouchDB  db_DB2  db_DynamoDB  db_Elasticsearch  \\\n",
       "19021         False       False   False        False             False   \n",
       "27335         False       False   False        False             False   \n",
       "38024         False       False   False        False             False   \n",
       "42889         False       False   False        False             False   \n",
       "42901         False       False   False        False             False   \n",
       "\n",
       "       db_FileMaker  db_Firebase  db_Firebird  db_Hbase  db_Informix  \\\n",
       "19021         False        False        False     False        False   \n",
       "27335         False        False        False     False        False   \n",
       "38024         False        False        False     False        False   \n",
       "42889         False        False        False     False        False   \n",
       "42901         False        False        False     False        False   \n",
       "\n",
       "       db_Ingres  db_MariaDB  db_Memcached  db_MongoDB  db_MySQL  db_Neo4j  \\\n",
       "19021      False       False         False       False     False     False   \n",
       "27335      False       False         False       False     False     False   \n",
       "38024      False       False         False       False      True     False   \n",
       "42889      False       False         False       False     False     False   \n",
       "42901      False       False         False       False     False     False   \n",
       "\n",
       "       db_Netezza  db_Oracle  db_PostgreSQL  db_Redis  db_Riak  db_SAP_HANA  \\\n",
       "19021       False      False          False     False    False        False   \n",
       "27335       False      False          False     False    False        False   \n",
       "38024       False       True          False     False    False        False   \n",
       "42889       False      False          False     False    False        False   \n",
       "42901       False      False          False     False    False        False   \n",
       "\n",
       "       db_SQL_Server  db_SQLite  db_Solr  db_Splunk  db_Sybase  db_Teradata  \\\n",
       "19021          False      False    False      False      False        False   \n",
       "27335          False      False    False      False      False        False   \n",
       "38024          False      False    False      False      False        False   \n",
       "42889          False      False    False      False      False        False   \n",
       "42901          False      False    False      False      False        False   \n",
       "\n",
       "       db_dBase edu  english experience  expert_adas  expert_blockchain  \\\n",
       "19021     False  大专    False         no        False              False   \n",
       "27335     False  本科    False         no        False              False   \n",
       "38024     False  本科    False        1_3        False              False   \n",
       "42889     False  本科     True         no        False              False   \n",
       "42901     False  本科    False         no        False              False   \n",
       "\n",
       "       expert_embed  expert_expert  expert_gis  _996_yes  _996_no  industry  \\\n",
       "19021         False          False       False     False     True       edu   \n",
       "27335         False          False       False      True    False  computer   \n",
       "38024         False          False       False     False    False  computer   \n",
       "42889         False          False       False     False     True  computer   \n",
       "42901         False          False       False     False    False  computer   \n",
       "\n",
       "       japanese                                    job_description  \\\n",
       "19021     False  月薪3500-8000底薪+补助+社保、五险一金、部分双休。部门免费包住，2.工作地点：可申...   \n",
       "27335     False  广州汇智通信技术有限公司                                  ...   \n",
       "38024     False  岗位职责1.按照上级计划和安排进行技术开发工作；2. 负责金融行业应用平台后端模块开发工作；...   \n",
       "42889      True  职位描述：1. 从事对日大型应用软件（证券、保险、银行、交通等）系统的详细设计、开发和测试等...   \n",
       "42901      True  职位描述：1. 从事对日大型应用软件（证券、保险、银行、交通等）系统的详细设计、开发和测试等...   \n",
       "\n",
       "                                            job_summary  \\\n",
       "19021                     广州-天河区|无工作经验|大专|招450人|03-13发布   \n",
       "27335                         广州|无工作经验|本科|招200人|03-31发布   \n",
       "38024                          深圳|1年经验|本科|招200人|03-26发布   \n",
       "42889  南京-鼓楼区|无工作经验|本科|招180人|03-19发布|英语良好|计算机科学与技术计算机网络   \n",
       "42901                     南京-鼓楼区|无工作经验|本科|招180人|03-19发布   \n",
       "\n",
       "                                                job_tags  phone_android  \\\n",
       "19021                                 绩效奖金,全勤奖,专业培训,节日福利          False   \n",
       "27335    五险一金,补充医疗保险,补充公积金,交通补贴,年终奖金,绩效奖金,通讯补贴,定期体检,餐饮补贴          False   \n",
       "38024                                五险一金,专业培训,年终奖金,员工旅游          False   \n",
       "42889  五险一金,员工旅游,交通补贴,餐饮补贴,专业培训,出国机会,绩效奖金,年终奖金,弹性工作,定期体检          False   \n",
       "42901  五险一金,员工旅游,交通补贴,餐饮补贴,专业培训,出国机会,绩效奖金,年终奖金,弹性工作,定期体检          False   \n",
       "\n",
       "       phone_app  phone_iso  pl_c_sharp  pl_cpp  pl_delphi  pl_go  pl_haskell  \\\n",
       "19021      False      False       False   False      False  False       False   \n",
       "27335       True       True        True    True      False  False       False   \n",
       "38024      False      False       False   False      False  False       False   \n",
       "42889      False      False        True    True      False  False       False   \n",
       "42901      False      False        True    True      False  False       False   \n",
       "\n",
       "       pl_java  pl_javascript  pl_julia  pl_kotlin  pl_lua  pl_matlab  \\\n",
       "19021    False          False     False      False   False      False   \n",
       "27335     True          False     False      False   False      False   \n",
       "38024     True          False     False      False   False      False   \n",
       "42889     True          False     False      False   False      False   \n",
       "42901     True          False     False      False   False      False   \n",
       "\n",
       "       pl_objective_c  pl_perl  pl_php  pl_python  pl_ruby  pl_rust  \\\n",
       "19021           False    False   False      False    False    False   \n",
       "27335           False    False   False      False    False    False   \n",
       "38024           False    False   False      False    False    False   \n",
       "42889           False    False   False      False    False    False   \n",
       "42901           False    False   False      False    False    False   \n",
       "\n",
       "       pl_scrala  pl_swift  pl_typescript  pl_vba  pl_visual_basic  \\\n",
       "19021      False     False          False   False            False   \n",
       "27335      False     False          False   False            False   \n",
       "38024      False     False          False   False            False   \n",
       "42889      False     False          False   False            False   \n",
       "42901      False     False          False   False            False   \n",
       "\n",
       "      publish_date  published_on_weekend  tag_baby_care  tag_five_insurance  \\\n",
       "19021   2019-03-13                 False          False               False   \n",
       "27335   2019-03-31                  True          False                True   \n",
       "38024   2019-03-26                 False          False                True   \n",
       "42889   2019-03-19                 False          False                True   \n",
       "42901   2019-03-19                 False          False                True   \n",
       "\n",
       "       tag_flexible  tag_no_overtime  tag_rest_one_day  tag_rest_two_days  \\\n",
       "19021         False            False             False              False   \n",
       "27335         False            False             False              False   \n",
       "38024         False            False             False              False   \n",
       "42889          True            False             False              False   \n",
       "42901          True            False             False              False   \n",
       "\n",
       "       tag_stock  \n",
       "19021      False  \n",
       "27335      False  \n",
       "38024      False  \n",
       "42889      False  \n",
       "42901      False  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.options.display.max_columns=100\n",
    "data.sort_values(by='headcount', ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 城市"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_82544580_69c3_11e9_ae67_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"col_heading level0 col0\" >city</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_95_min</th> \n",
       "        <th class=\"col_heading level0 col3\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col4\" >salary_95_max</th> \n",
       "        <th class=\"col_heading level0 col5\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col6\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow0_col0\" class=\"data row0 col0\" >beijing</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow0_col1\" class=\"data row0 col1\" >16277</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow0_col2\" class=\"data row0 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow0_col3\" class=\"data row0 col3\" >13000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow0_col4\" class=\"data row0 col4\" >40000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow0_col5\" class=\"data row0 col5\" >28346</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow0_col6\" class=\"data row0 col6\" >17.62%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow1_col0\" class=\"data row1 col0\" >shanghai</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow1_col1\" class=\"data row1 col1\" >15842</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow1_col2\" class=\"data row1 col2\" >5250</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow1_col3\" class=\"data row1 col3\" >14583</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow1_col4\" class=\"data row1 col4\" >35000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow1_col5\" class=\"data row1 col5\" >33078</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow1_col6\" class=\"data row1 col6\" >20.57%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow2_col0\" class=\"data row2 col0\" >shenzhen</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow2_col1\" class=\"data row2 col1\" >15324</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow2_col2\" class=\"data row2 col2\" >5250</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow2_col3\" class=\"data row2 col3\" >13500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow2_col4\" class=\"data row2 col4\" >33333</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow2_col5\" class=\"data row2 col5\" >19659</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow2_col6\" class=\"data row2 col6\" >12.22%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow3_col0\" class=\"data row3 col0\" >hangzhou</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow3_col1\" class=\"data row3 col1\" >15024</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow3_col2\" class=\"data row3 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow3_col3\" class=\"data row3 col3\" >12500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow3_col4\" class=\"data row3 col4\" >35000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow3_col5\" class=\"data row3 col5\" >8508</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow3_col6\" class=\"data row3 col6\" >5.29%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow4_col0\" class=\"data row4 col0\" >chengdu</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow4_col1\" class=\"data row4 col1\" >12653</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow4_col2\" class=\"data row4 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow4_col3\" class=\"data row4 col3\" >11500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow4_col4\" class=\"data row4 col4\" >30000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow4_col5\" class=\"data row4 col5\" >7522</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow4_col6\" class=\"data row4 col6\" >4.68%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow5_col0\" class=\"data row5 col0\" >guangzhou</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow5_col1\" class=\"data row5 col1\" >12602</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow5_col2\" class=\"data row5 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow5_col3\" class=\"data row5 col3\" >11500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow5_col4\" class=\"data row5 col4\" >30000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow5_col5\" class=\"data row5 col5\" >15715</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow5_col6\" class=\"data row5 col6\" >9.77%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow6_col0\" class=\"data row6 col0\" >nanjing</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow6_col1\" class=\"data row6 col1\" >12386</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow6_col2\" class=\"data row6 col2\" >5000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow6_col3\" class=\"data row6 col3\" >11500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow6_col4\" class=\"data row6 col4\" >28475</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow6_col5\" class=\"data row6 col5\" >8743</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow6_col6\" class=\"data row6 col6\" >5.44%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow7_col0\" class=\"data row7 col0\" >tianjin</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow7_col1\" class=\"data row7 col1\" >12241</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow7_col2\" class=\"data row7 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow7_col3\" class=\"data row7 col3\" >10885</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow7_col4\" class=\"data row7 col4\" >30000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow7_col5\" class=\"data row7 col5\" >1122</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow7_col6\" class=\"data row7 col6\" >0.70%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow8_col0\" class=\"data row8 col0\" >ningbo</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow8_col1\" class=\"data row8 col1\" >11237</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow8_col2\" class=\"data row8 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow8_col3\" class=\"data row8 col3\" >9500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow8_col4\" class=\"data row8 col4\" >29167</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow8_col5\" class=\"data row8 col5\" >1002</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow8_col6\" class=\"data row8 col6\" >0.62%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow9_col0\" class=\"data row9 col0\" >xian</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow9_col1\" class=\"data row9 col1\" >11030</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow9_col2\" class=\"data row9 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow9_col3\" class=\"data row9 col3\" >10000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow9_col4\" class=\"data row9 col4\" >27500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow9_col5\" class=\"data row9 col5\" >3934</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow9_col6\" class=\"data row9 col6\" >2.45%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow10_col0\" class=\"data row10 col0\" >wuhan</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow10_col1\" class=\"data row10 col1\" >10995</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow10_col2\" class=\"data row10 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow10_col3\" class=\"data row10 col3\" >10417</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow10_col4\" class=\"data row10 col4\" >22500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow10_col5\" class=\"data row10 col5\" >8270</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow10_col6\" class=\"data row10 col6\" >5.14%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow11_col0\" class=\"data row11 col0\" >changsha</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow11_col1\" class=\"data row11 col1\" >10780</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow11_col2\" class=\"data row11 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow11_col3\" class=\"data row11 col3\" >10000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow11_col4\" class=\"data row11 col4\" >22500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow11_col5\" class=\"data row11 col5\" >3789</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow11_col6\" class=\"data row11 col6\" >2.36%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow12_col0\" class=\"data row12 col0\" >fuzhou</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow12_col1\" class=\"data row12 col1\" >10626</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow12_col2\" class=\"data row12 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow12_col3\" class=\"data row12 col3\" >10000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow12_col4\" class=\"data row12 col4\" >25000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow12_col5\" class=\"data row12 col5\" >2077</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow12_col6\" class=\"data row12 col6\" >1.29%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow13_col0\" class=\"data row13 col0\" >dongguan</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow13_col1\" class=\"data row13 col1\" >10509</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow13_col2\" class=\"data row13 col2\" >3635</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow13_col3\" class=\"data row13 col3\" >9000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow13_col4\" class=\"data row13 col4\" >24117</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow13_col5\" class=\"data row13 col5\" >1205</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow13_col6\" class=\"data row13 col6\" >0.75%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow14_col0\" class=\"data row14 col0\" >chongqing</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow14_col1\" class=\"data row14 col1\" >10390</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow14_col2\" class=\"data row14 col2\" >4000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow14_col3\" class=\"data row14 col3\" >9000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow14_col4\" class=\"data row14 col4\" >22500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow14_col5\" class=\"data row14 col5\" >2628</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow14_col6\" class=\"data row14 col6\" >1.63%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow15_col0\" class=\"data row15 col0\" >changchun</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow15_col1\" class=\"data row15 col1\" >10093</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow15_col2\" class=\"data row15 col2\" >3403</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow15_col3\" class=\"data row15 col3\" >8000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow15_col4\" class=\"data row15 col4\" >34275</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow15_col5\" class=\"data row15 col5\" >529</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow15_col6\" class=\"data row15 col6\" >0.33%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow16_col0\" class=\"data row16 col0\" >dalian</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow16_col1\" class=\"data row16 col1\" >9707</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow16_col2\" class=\"data row16 col2\" >2500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow16_col3\" class=\"data row16 col3\" >9000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow16_col4\" class=\"data row16 col4\" >25000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow16_col5\" class=\"data row16 col5\" >3399</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow16_col6\" class=\"data row16 col6\" >2.11%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow17_col0\" class=\"data row17 col0\" >jinan</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow17_col1\" class=\"data row17 col1\" >9627</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow17_col2\" class=\"data row17 col2\" >3500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow17_col3\" class=\"data row17 col3\" >8000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow17_col4\" class=\"data row17 col4\" >25000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow17_col5\" class=\"data row17 col5\" >1517</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow17_col6\" class=\"data row17 col6\" >0.94%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow18_col0\" class=\"data row18 col0\" >hefei</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow18_col1\" class=\"data row18 col1\" >9430</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow18_col2\" class=\"data row18 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow18_col3\" class=\"data row18 col3\" >9000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow18_col4\" class=\"data row18 col4\" >22500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow18_col5\" class=\"data row18 col5\" >1975</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow18_col6\" class=\"data row18 col6\" >1.23%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow19_col0\" class=\"data row19 col0\" >qingdao</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow19_col1\" class=\"data row19 col1\" >8985</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow19_col2\" class=\"data row19 col2\" >4084</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow19_col3\" class=\"data row19 col3\" >8000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow19_col4\" class=\"data row19 col4\" >19051</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow19_col5\" class=\"data row19 col5\" >1327</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow19_col6\" class=\"data row19 col6\" >0.83%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow20_col0\" class=\"data row20 col0\" >shenyang</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow20_col1\" class=\"data row20 col1\" >8521</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow20_col2\" class=\"data row20 col2\" >2636</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow20_col3\" class=\"data row20 col3\" >7000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow20_col4\" class=\"data row20 col4\" >20000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow20_col5\" class=\"data row20 col5\" >1290</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow20_col6\" class=\"data row20 col6\" >0.80%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow21_col0\" class=\"data row21 col0\" >harbin</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow21_col1\" class=\"data row21 col1\" >8437</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow21_col2\" class=\"data row21 col2\" >2500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow21_col3\" class=\"data row21 col3\" >7500</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow21_col4\" class=\"data row21 col4\" >19107</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow21_col5\" class=\"data row21 col5\" >570</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow21_col6\" class=\"data row21 col6\" >0.35%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow22_col0\" class=\"data row22 col0\" >zhengzhou</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow22_col1\" class=\"data row22 col1\" >8021</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow22_col2\" class=\"data row22 col2\" >4000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow22_col3\" class=\"data row22 col3\" >7000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow22_col4\" class=\"data row22 col4\" >18000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow22_col5\" class=\"data row22 col5\" >3779</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow22_col6\" class=\"data row22 col6\" >2.35%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow23_col0\" class=\"data row23 col0\" >kunming</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow23_col1\" class=\"data row23 col1\" >7897</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow23_col2\" class=\"data row23 col2\" >3750</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow23_col3\" class=\"data row23 col3\" >7000</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow23_col4\" class=\"data row23 col4\" >17156</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow23_col5\" class=\"data row23 col5\" >849</td> \n",
       "        <td id=\"T_82544580_69c3_11e9_ae67_701ce71031efrow23_col6\" class=\"data row23 col6\" >0.53%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x23331412c18>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_pl=get_sub_stats_by_col(data,'city')\n",
    "apply_style(data_pl)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 编程语言"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_93f165b8_69c3_11e9_af57_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"col_heading level0 col0\" >rank</th> \n",
       "        <th class=\"col_heading level0 col1\" >pl_</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col3\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col4\" >salary_95_min</th> \n",
       "        <th class=\"col_heading level0 col5\" >salary_95_max</th> \n",
       "        <th class=\"col_heading level0 col6\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col7\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow0_col0\" class=\"data row0 col0\" >1</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow0_col1\" class=\"data row0 col1\" >haskell</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow0_col2\" class=\"data row0 col2\" >27772</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow0_col3\" class=\"data row0 col3\" >30667</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow0_col4\" class=\"data row0 col4\" >7544</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow0_col5\" class=\"data row0 col5\" >45000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow0_col6\" class=\"data row0 col6\" >41</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow0_col7\" class=\"data row0 col7\" >0.02%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow1_col0\" class=\"data row1 col0\" >2</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow1_col1\" class=\"data row1 col1\" >julia</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow1_col2\" class=\"data row1 col2\" >26875</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow1_col3\" class=\"data row1 col3\" >26875</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow1_col4\" class=\"data row1 col4\" >17500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow1_col5\" class=\"data row1 col5\" >30000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow1_col6\" class=\"data row1 col6\" >4</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow1_col7\" class=\"data row1 col7\" >0.00%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow2_col0\" class=\"data row2 col0\" >3</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow2_col1\" class=\"data row2 col1\" >rust</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow2_col2\" class=\"data row2 col2\" >19567</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow2_col3\" class=\"data row2 col3\" >17000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow2_col4\" class=\"data row2 col4\" >6500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow2_col5\" class=\"data row2 col5\" >45833</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow2_col6\" class=\"data row2 col6\" >242</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow2_col7\" class=\"data row2 col7\" >0.11%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow3_col0\" class=\"data row3 col0\" >4</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow3_col1\" class=\"data row3 col1\" >python</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow3_col2\" class=\"data row3 col2\" >18315</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow3_col3\" class=\"data row3 col3\" >16000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow3_col4\" class=\"data row3 col4\" >4000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow3_col5\" class=\"data row3 col5\" >42500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow3_col6\" class=\"data row3 col6\" >17854</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow3_col7\" class=\"data row3 col7\" >8.04%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow4_col0\" class=\"data row4 col0\" >5</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow4_col1\" class=\"data row4 col1\" >matlab</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow4_col2\" class=\"data row4 col2\" >18285</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow4_col3\" class=\"data row4 col3\" >17500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow4_col4\" class=\"data row4 col4\" >5000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow4_col5\" class=\"data row4 col5\" >40000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow4_col6\" class=\"data row4 col6\" >3304</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow4_col7\" class=\"data row4 col7\" >1.49%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow5_col0\" class=\"data row5 col0\" >6</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow5_col1\" class=\"data row5 col1\" >perl</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow5_col2\" class=\"data row5 col2\" >17845</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow5_col3\" class=\"data row5 col3\" >15000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow5_col4\" class=\"data row5 col4\" >3750</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow5_col5\" class=\"data row5 col5\" >40000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow5_col6\" class=\"data row5 col6\" >1681</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow5_col7\" class=\"data row5 col7\" >0.76%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow6_col0\" class=\"data row6 col0\" >7</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow6_col1\" class=\"data row6 col1\" >go</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow6_col2\" class=\"data row6 col2\" >17688</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow6_col3\" class=\"data row6 col3\" >15000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow6_col4\" class=\"data row6 col4\" >6000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow6_col5\" class=\"data row6 col5\" >39988</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow6_col6\" class=\"data row6 col6\" >15426</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow6_col7\" class=\"data row6 col7\" >6.95%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow7_col0\" class=\"data row7 col0\" >8</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow7_col1\" class=\"data row7 col1\" >ruby</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow7_col2\" class=\"data row7 col2\" >16402</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow7_col3\" class=\"data row7 col3\" >16000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow7_col4\" class=\"data row7 col4\" >4508</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow7_col5\" class=\"data row7 col5\" >31323</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow7_col6\" class=\"data row7 col6\" >733</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow7_col7\" class=\"data row7 col7\" >0.33%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow8_col0\" class=\"data row8 col0\" >9</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow8_col1\" class=\"data row8 col1\" >lua</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow8_col2\" class=\"data row8 col2\" >16259</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow8_col3\" class=\"data row8 col3\" >15000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow8_col4\" class=\"data row8 col4\" >5250</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow8_col5\" class=\"data row8 col5\" >35000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow8_col6\" class=\"data row8 col6\" >2465</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow8_col7\" class=\"data row8 col7\" >1.11%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow9_col0\" class=\"data row9 col0\" >10</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow9_col1\" class=\"data row9 col1\" >cpp</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow9_col2\" class=\"data row9 col2\" >15957</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow9_col3\" class=\"data row9 col3\" >13000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow9_col4\" class=\"data row9 col4\" >4000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow9_col5\" class=\"data row9 col5\" >37500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow9_col6\" class=\"data row9 col6\" >35622</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow9_col7\" class=\"data row9 col7\" >16.04%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow10_col0\" class=\"data row10 col0\" >11</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow10_col1\" class=\"data row10 col1\" >typescript</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow10_col2\" class=\"data row10 col2\" >14758</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow10_col3\" class=\"data row10 col3\" >13750</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow10_col4\" class=\"data row10 col4\" >6000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow10_col5\" class=\"data row10 col5\" >30000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow10_col6\" class=\"data row10 col6\" >610</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow10_col7\" class=\"data row10 col7\" >0.27%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow11_col0\" class=\"data row11 col0\" >12</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow11_col1\" class=\"data row11 col1\" >kotlin</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow11_col2\" class=\"data row11 col2\" >14721</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow11_col3\" class=\"data row11 col3\" >12500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow11_col4\" class=\"data row11 col4\" >6102</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow11_col5\" class=\"data row11 col5\" >30000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow11_col6\" class=\"data row11 col6\" >501</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow11_col7\" class=\"data row11 col7\" >0.23%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow12_col0\" class=\"data row12 col0\" >13</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow12_col1\" class=\"data row12 col1\" >swift</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow12_col2\" class=\"data row12 col2\" >14127</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow12_col3\" class=\"data row12 col3\" >12500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow12_col4\" class=\"data row12 col4\" >5259</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow12_col5\" class=\"data row12 col5\" >30000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow12_col6\" class=\"data row12 col6\" >1645</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow12_col7\" class=\"data row12 col7\" >0.74%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow13_col0\" class=\"data row13 col0\" >14</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow13_col1\" class=\"data row13 col1\" >java</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow13_col2\" class=\"data row13 col2\" >13836</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow13_col3\" class=\"data row13 col3\" >12500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow13_col4\" class=\"data row13 col4\" >3750</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow13_col5\" class=\"data row13 col5\" >32500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow13_col6\" class=\"data row13 col6\" >73081</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow13_col7\" class=\"data row13 col7\" >32.90%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow14_col0\" class=\"data row14 col0\" >15</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow14_col1\" class=\"data row14 col1\" >objective_c</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow14_col2\" class=\"data row14 col2\" >13498</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow14_col3\" class=\"data row14 col3\" >12500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow14_col4\" class=\"data row14 col4\" >5250</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow14_col5\" class=\"data row14 col5\" >23250</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow14_col6\" class=\"data row14 col6\" >265</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow14_col7\" class=\"data row14 col7\" >0.12%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow15_col0\" class=\"data row15 col0\" >16</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow15_col1\" class=\"data row15 col1\" >php</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow15_col2\" class=\"data row15 col2\" >12683</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow15_col3\" class=\"data row15 col3\" >11500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow15_col4\" class=\"data row15 col4\" >3750</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow15_col5\" class=\"data row15 col5\" >31525</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow15_col6\" class=\"data row15 col6\" >10630</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow15_col7\" class=\"data row15 col7\" >4.79%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow16_col0\" class=\"data row16 col0\" >17</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow16_col1\" class=\"data row16 col1\" >javascript</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow16_col2\" class=\"data row16 col2\" >12112</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow16_col3\" class=\"data row16 col3\" >11500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow16_col4\" class=\"data row16 col4\" >4000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow16_col5\" class=\"data row16 col5\" >25000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow16_col6\" class=\"data row16 col6\" >29523</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow16_col7\" class=\"data row16 col7\" >13.29%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow17_col0\" class=\"data row17 col0\" >18</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow17_col1\" class=\"data row17 col1\" >c_sharp</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow17_col2\" class=\"data row17 col2\" >11628</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow17_col3\" class=\"data row17 col3\" >11000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow17_col4\" class=\"data row17 col4\" >3750</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow17_col5\" class=\"data row17 col5\" >24000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow17_col6\" class=\"data row17 col6\" >27370</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow17_col7\" class=\"data row17 col7\" >12.32%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow18_col0\" class=\"data row18 col0\" >19</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow18_col1\" class=\"data row18 col1\" >vba</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow18_col2\" class=\"data row18 col2\" >11015</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow18_col3\" class=\"data row18 col3\" >11500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow18_col4\" class=\"data row18 col4\" >2500</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow18_col5\" class=\"data row18 col5\" >20000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow18_col6\" class=\"data row18 col6\" >237</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow18_col7\" class=\"data row18 col7\" >0.11%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow19_col0\" class=\"data row19 col0\" >20</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow19_col1\" class=\"data row19 col1\" >delphi</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow19_col2\" class=\"data row19 col2\" >9908</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow19_col3\" class=\"data row19 col3\" >9000</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow19_col4\" class=\"data row19 col4\" >4552</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow19_col5\" class=\"data row19 col5\" >19258</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow19_col6\" class=\"data row19 col6\" >849</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow19_col7\" class=\"data row19 col7\" >0.38%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow20_col0\" class=\"data row20 col0\" >21</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow20_col1\" class=\"data row20 col1\" >visual_basic</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow20_col2\" class=\"data row20 col2\" >9474</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow20_col3\" class=\"data row20 col3\" >8867</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow20_col4\" class=\"data row20 col4\" >6419</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow20_col5\" class=\"data row20 col5\" >16375</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow20_col6\" class=\"data row20 col6\" >29</td> \n",
       "        <td id=\"T_93f165b8_69c3_11e9_af57_701ce71031efrow20_col7\" class=\"data row20 col7\" >0.01%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x23331412588>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_pl=get_sub_stats_by_prefix(data,'pl_')\n",
    "apply_style(data_pl)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据显示，haskell才是最赚钱的编程语言。python是主流语言里面最赚钱的，比java的工资多了3000元！vb是最不赚钱的了。其中，最赚钱的编程语言和最不赚钱的，工资居然差了2倍。所以，要选好编程语言呀！"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 教育"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_9ce96b74_69c3_11e9_900f_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"col_heading level0 col0\" >edu</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_95_min</th> \n",
       "        <th class=\"col_heading level0 col3\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col4\" >salary_95_max</th> \n",
       "        <th class=\"col_heading level0 col5\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col6\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow0_col0\" class=\"data row0 col0\" >博士</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow0_col1\" class=\"data row0 col1\" >27674</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow0_col2\" class=\"data row0 col2\" >12500</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow0_col3\" class=\"data row0 col3\" >25000</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow0_col4\" class=\"data row0 col4\" >55000</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow0_col5\" class=\"data row0 col5\" >191</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow0_col6\" class=\"data row0 col6\" >0.15%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow1_col0\" class=\"data row1 col0\" >硕士</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow1_col1\" class=\"data row1 col1\" >20194</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow1_col2\" class=\"data row1 col2\" >5250</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow1_col3\" class=\"data row1 col3\" >17500</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow1_col4\" class=\"data row1 col4\" >45000</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow1_col5\" class=\"data row1 col5\" >4409</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow1_col6\" class=\"data row1 col6\" >3.36%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow2_col0\" class=\"data row2 col0\" >本科</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow2_col1\" class=\"data row2 col1\" >14872</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow2_col2\" class=\"data row2 col2\" >4500</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow2_col3\" class=\"data row2 col3\" >12500</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow2_col4\" class=\"data row2 col4\" >35000</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow2_col5\" class=\"data row2 col5\" >83576</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow2_col6\" class=\"data row2 col6\" >63.76%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow3_col0\" class=\"data row3 col0\" >大专</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow3_col1\" class=\"data row3 col1\" >11251</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow3_col2\" class=\"data row3 col2\" >3750</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow3_col3\" class=\"data row3 col3\" >10000</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow3_col4\" class=\"data row3 col4\" >25000</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow3_col5\" class=\"data row3 col5\" >42902</td> \n",
       "        <td id=\"T_9ce96b74_69c3_11e9_900f_701ce71031efrow3_col6\" class=\"data row3 col6\" >32.73%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x233337bcb70>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_edu=get_sub_stats_by_col(data[data.edu.isin(['大专','本科','硕士','博士'])], 'edu')\n",
    "apply_style(data_edu)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "salary_associate=data[data.edu=='大专'].monthly_salary\n",
    "salary_bachelor=data[data.edu=='本科'].monthly_salary\n",
    "salary_master=data[data.edu=='硕士'].monthly_salary\n",
    "salary_phd=data[data.edu=='博士'].monthly_salary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "大专，本科，硕士，博士的平均工资分别是11649，15318，20520，27720。中位数分别是11000， 13000，17917， 26042。\n"
     ]
    }
   ],
   "source": [
    "print('大专，本科，硕士，博士的平均工资分别是{:.0f}，{:.0f}，{:.0f}，{:.0f}。中位数分别是{:.0f}， {:.0f}，{:.0f}， {:.0f}。'.format(\n",
    "    salary_associate.mean(),salary_bachelor.mean(),salary_master.mean(),salary_phd.mean(),\n",
    "    salary_associate.median(),salary_bachelor.median(),salary_master.median(),salary_phd.median()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=29.67863061167002, pvalue=5.922489910603948e-08)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.f_oneway(salary_phd, salary_master)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=612.2777905826467, pvalue=1.2411237644249955e-133)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.f_oneway(salary_master, salary_bachelor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=2238.310922947605, pvalue=0.0)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.f_oneway(salary_bachelor, salary_associate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "经过Oneway Anova Test，证明从大专到博士，学历每提高一级，工资都有显著的提高。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "order=['大专','本科','硕士','博士']\n",
    "a=sns.boxplot(y='edu',x='monthly_salary',order=order,data=data[data.edu.isin(order)], orient='h')\n",
    "plt.annotate('https://github.com/juwikuang/job_survey', xy=(0.5,1.5), xytext=(2, 1.55))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 工作经验 Working Experience"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"col_heading level0 col0\" >experience</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_95_min</th> \n",
       "        <th class=\"col_heading level0 col3\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col4\" >salary_95_max</th> \n",
       "        <th class=\"col_heading level0 col5\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col6\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow0_col0\" class=\"data row0 col0\" >10+</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow0_col1\" class=\"data row0 col1\" >29981</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow0_col2\" class=\"data row0 col2\" >12500</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow0_col3\" class=\"data row0 col3\" >27500</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow0_col4\" class=\"data row0 col4\" >60000</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow0_col5\" class=\"data row0 col5\" >338</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow0_col6\" class=\"data row0 col6\" >0.21%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow1_col0\" class=\"data row1 col0\" >5_10</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow1_col1\" class=\"data row1 col1\" >20687</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow1_col2\" class=\"data row1 col2\" >9000</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow1_col3\" class=\"data row1 col3\" >19500</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow1_col4\" class=\"data row1 col4\" >41667</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow1_col5\" class=\"data row1 col5\" >16832</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow1_col6\" class=\"data row1 col6\" >10.47%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow2_col0\" class=\"data row2 col0\" >3_5</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow2_col1\" class=\"data row2 col1\" >15595</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow2_col2\" class=\"data row2 col2\" >7000</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow2_col3\" class=\"data row2 col3\" >13500</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow2_col4\" class=\"data row2 col4\" >35000</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow2_col5\" class=\"data row2 col5\" >44789</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow2_col6\" class=\"data row2 col6\" >27.85%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow3_col0\" class=\"data row3 col0\" >no</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow3_col1\" class=\"data row3 col1\" >11830</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow3_col2\" class=\"data row3 col2\" >3000</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow3_col3\" class=\"data row3 col3\" >10000</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow3_col4\" class=\"data row3 col4\" >30000</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow3_col5\" class=\"data row3 col5\" >52672</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow3_col6\" class=\"data row3 col6\" >32.75%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow4_col0\" class=\"data row4 col0\" >1_3</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow4_col1\" class=\"data row4 col1\" >11570</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow4_col2\" class=\"data row4 col2\" >5000</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow4_col3\" class=\"data row4 col3\" >10500</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow4_col4\" class=\"data row4 col4\" >26612</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow4_col5\" class=\"data row4 col5\" >46202</td> \n",
       "        <td id=\"T_a23207dc_69c3_11e9_a7f0_701ce71031efrow4_col6\" class=\"data row4 col6\" >28.73%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x233337049b0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_experience=get_sub_stats_by_col(data, 'experience')\n",
    "apply_style(data_experience)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "salary_we_10=data[data.experience=='10+'].monthly_salary\n",
    "salary_we_5_10=data[data.experience=='5_10'].monthly_salary\n",
    "salary_we_3_5=data[data.experience=='3_5'].monthly_salary\n",
    "salary_we_1_3=data[data.experience=='1_3'].monthly_salary\n",
    "salary_we_no=data[data.experience=='no'].monthly_salary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "order=['10+','5_10','3_5','1_3']\n",
    "sns.boxplot(y='experience',x='monthly_salary',order=order,data=data[data.experience.isin(order)], orient='h')\n",
    "plt.annotate('https://github.com/juwikuang/job_survey', xy=(1.5,1.5), xytext=(1.55, 1.55))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 公司 Company"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 公司性质 Company Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_a4624b02_69c3_11e9_aafb_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"col_heading level0 col0\" >company_type</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_95_min</th> \n",
       "        <th class=\"col_heading level0 col3\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col4\" >salary_95_max</th> \n",
       "        <th class=\"col_heading level0 col5\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col6\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow0_col0\" class=\"data row0 col0\" >外资（欧美）</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow0_col1\" class=\"data row0 col1\" >16236</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow0_col2\" class=\"data row0 col2\" >3750</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow0_col3\" class=\"data row0 col3\" >15000</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow0_col4\" class=\"data row0 col4\" >37500</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow0_col5\" class=\"data row0 col5\" >7940</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow0_col6\" class=\"data row0 col6\" >4.94%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow1_col0\" class=\"data row1 col0\" >合资</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow1_col1\" class=\"data row1 col1\" >15227</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow1_col2\" class=\"data row1 col2\" >4235</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow1_col3\" class=\"data row1 col3\" >13500</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow1_col4\" class=\"data row1 col4\" >32500</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow1_col5\" class=\"data row1 col5\" >13491</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow1_col6\" class=\"data row1 col6\" >8.39%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow2_col0\" class=\"data row2 col0\" >外企代表处</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow2_col1\" class=\"data row2 col1\" >15182</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow2_col2\" class=\"data row2 col2\" >7050</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow2_col3\" class=\"data row2 col3\" >13083</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow2_col4\" class=\"data row2 col4\" >29150</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow2_col5\" class=\"data row2 col5\" >141</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow2_col6\" class=\"data row2 col6\" >0.09%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow3_col0\" class=\"data row3 col0\" >外资（非欧美）</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow3_col1\" class=\"data row3 col1\" >13996</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow3_col2\" class=\"data row3 col2\" >3704</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow3_col3\" class=\"data row3 col3\" >12500</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow3_col4\" class=\"data row3 col4\" >30000</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow3_col5\" class=\"data row3 col5\" >7770</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow3_col6\" class=\"data row3 col6\" >4.83%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow4_col0\" class=\"data row4 col0\" >民营公司</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow4_col1\" class=\"data row4 col1\" >13470</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow4_col2\" class=\"data row4 col2\" >3750</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow4_col3\" class=\"data row4 col3\" >12500</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow4_col4\" class=\"data row4 col4\" >34500</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow4_col5\" class=\"data row4 col5\" >117430</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow4_col6\" class=\"data row4 col6\" >73.01%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow5_col0\" class=\"data row5 col0\" >国企</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow5_col1\" class=\"data row5 col1\" >13443</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow5_col2\" class=\"data row5 col2\" >5000</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow5_col3\" class=\"data row5 col3\" >12500</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow5_col4\" class=\"data row5 col4\" >27500</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow5_col5\" class=\"data row5 col5\" >12261</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow5_col6\" class=\"data row5 col6\" >7.62%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow6_col0\" class=\"data row6 col0\" >事业单位</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow6_col1\" class=\"data row6 col1\" >13385</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow6_col2\" class=\"data row6 col2\" >5069</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow6_col3\" class=\"data row6 col3\" >12500</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow6_col4\" class=\"data row6 col4\" >29167</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow6_col5\" class=\"data row6 col5\" >1498</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow6_col6\" class=\"data row6 col6\" >0.93%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow7_col0\" class=\"data row7 col0\" >非营利组织</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow7_col1\" class=\"data row7 col1\" >9394</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow7_col2\" class=\"data row7 col2\" >2729</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow7_col3\" class=\"data row7 col3\" >10069</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow7_col4\" class=\"data row7 col4\" >16500</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow7_col5\" class=\"data row7 col5\" >116</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow7_col6\" class=\"data row7 col6\" >0.07%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow8_col0\" class=\"data row8 col0\" >政府机关</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow8_col1\" class=\"data row8 col1\" >8233</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow8_col2\" class=\"data row8 col2\" >5250</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow8_col3\" class=\"data row8 col3\" >7000</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow8_col4\" class=\"data row8 col4\" >20833</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow8_col5\" class=\"data row8 col5\" >186</td> \n",
       "        <td id=\"T_a4624b02_69c3_11e9_aafb_701ce71031efrow8_col6\" class=\"data row8 col6\" >0.12%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x23325404fd0>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_company_type=get_sub_stats_by_col(data,'company_type')\n",
    "apply_style(data_company_type)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "us_eu是欧美外企，startup是创业公司，listed是上市公司，state是国企，private是私企，foreign是非欧美外企，其他不足1000个样本的不管了。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 公司规模 Company Size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_a5f02498_69c3_11e9_9797_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"col_heading level0 col0\" >company_size</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_95_min</th> \n",
       "        <th class=\"col_heading level0 col3\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col4\" >salary_95_max</th> \n",
       "        <th class=\"col_heading level0 col5\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col6\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow0_col0\" class=\"data row0 col0\" >10000+</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow0_col1\" class=\"data row0 col1\" >18278</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow0_col2\" class=\"data row0 col2\" >3500</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow0_col3\" class=\"data row0 col3\" >15000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow0_col4\" class=\"data row0 col4\" >45000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow0_col5\" class=\"data row0 col5\" >7344</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow0_col6\" class=\"data row0 col6\" >4.57%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow1_col0\" class=\"data row1 col0\" ></td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow1_col1\" class=\"data row1 col1\" >15860</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow1_col2\" class=\"data row1 col2\" >5250</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow1_col3\" class=\"data row1 col3\" >12500</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow1_col4\" class=\"data row1 col4\" >50000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow1_col5\" class=\"data row1 col5\" >698</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow1_col6\" class=\"data row1 col6\" >0.43%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow2_col0\" class=\"data row2 col0\" >5000-10000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow2_col1\" class=\"data row2 col1\" >15421</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow2_col2\" class=\"data row2 col2\" >5250</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow2_col3\" class=\"data row2 col3\" >15000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow2_col4\" class=\"data row2 col4\" >32010</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow2_col5\" class=\"data row2 col5\" >3467</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow2_col6\" class=\"data row2 col6\" >2.16%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow3_col0\" class=\"data row3 col0\" >500-1000人</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow3_col1\" class=\"data row3 col1\" >15199</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow3_col2\" class=\"data row3 col2\" >5000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow3_col3\" class=\"data row3 col3\" >12500</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow3_col4\" class=\"data row3 col4\" >40000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow3_col5\" class=\"data row3 col5\" >16469</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow3_col6\" class=\"data row3 col6\" >10.24%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow4_col0\" class=\"data row4 col0\" >1000-5000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow4_col1\" class=\"data row4 col1\" >14370</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow4_col2\" class=\"data row4 col2\" >5000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow4_col3\" class=\"data row4 col3\" >12500</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow4_col4\" class=\"data row4 col4\" >35000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow4_col5\" class=\"data row4 col5\" >20910</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow4_col6\" class=\"data row4 col6\" >13.00%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow5_col0\" class=\"data row5 col0\" >150-500</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow5_col1\" class=\"data row5 col1\" >13785</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow5_col2\" class=\"data row5 col2\" >3750</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow5_col3\" class=\"data row5 col3\" >12500</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow5_col4\" class=\"data row5 col4\" >30500</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow5_col5\" class=\"data row5 col5\" >33445</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow5_col6\" class=\"data row5 col6\" >20.79%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow6_col0\" class=\"data row6 col0\" >50-150</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow6_col1\" class=\"data row6 col1\" >13060</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow6_col2\" class=\"data row6 col2\" >3750</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow6_col3\" class=\"data row6 col3\" >12500</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow6_col4\" class=\"data row6 col4\" >32500</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow6_col5\" class=\"data row6 col5\" >48786</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow6_col6\" class=\"data row6 col6\" >30.33%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow7_col0\" class=\"data row7 col0\" >50-</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow7_col1\" class=\"data row7 col1\" >12344</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow7_col2\" class=\"data row7 col2\" >3750</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow7_col3\" class=\"data row7 col3\" >11500</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow7_col4\" class=\"data row7 col4\" >30000</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow7_col5\" class=\"data row7 col5\" >29714</td> \n",
       "        <td id=\"T_a5f02498_69c3_11e9_9797_701ce71031efrow7_col6\" class=\"data row7 col6\" >18.48%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x233336fada0>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_company_size=get_sub_stats_by_col(data,'company_size')\n",
    "apply_style(data_company_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "公司越大，工资越高"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 行业 Industry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_a742ebae_69c3_11e9_9120_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"col_heading level0 col0\" >industry</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_95_min</th> \n",
       "        <th class=\"col_heading level0 col3\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col4\" >salary_95_max</th> \n",
       "        <th class=\"col_heading level0 col5\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col6\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow0_col0\" class=\"data row0 col0\" >finance</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow0_col1\" class=\"data row0 col1\" >15357</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow0_col2\" class=\"data row0 col2\" >5211</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow0_col3\" class=\"data row0 col3\" >14000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow0_col4\" class=\"data row0 col4\" >32500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow0_col5\" class=\"data row0 col5\" >5229</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow0_col6\" class=\"data row0 col6\" >3.25%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow1_col0\" class=\"data row1 col0\" >service</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow1_col1\" class=\"data row1 col1\" >14604</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow1_col2\" class=\"data row1 col2\" >5000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow1_col3\" class=\"data row1 col3\" >12500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow1_col4\" class=\"data row1 col4\" >35393</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow1_col5\" class=\"data row1 col5\" >958</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow1_col6\" class=\"data row1 col6\" >0.60%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow2_col0\" class=\"data row2 col0\" >edu</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow2_col1\" class=\"data row2 col1\" >14152</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow2_col2\" class=\"data row2 col2\" >3750</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow2_col3\" class=\"data row2 col3\" >12500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow2_col4\" class=\"data row2 col4\" >35000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow2_col5\" class=\"data row2 col5\" >10139</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow2_col6\" class=\"data row2 col6\" >6.30%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow3_col0\" class=\"data row3 col0\" >trade</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow3_col1\" class=\"data row3 col1\" >14137</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow3_col2\" class=\"data row3 col2\" >5000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow3_col3\" class=\"data row3 col3\" >12500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow3_col4\" class=\"data row3 col4\" >35000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow3_col5\" class=\"data row3 col5\" >7340</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow3_col6\" class=\"data row3 col6\" >4.56%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow4_col0\" class=\"data row4 col0\" >logistic</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow4_col1\" class=\"data row4 col1\" >13938</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow4_col2\" class=\"data row4 col2\" >5000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow4_col3\" class=\"data row4 col3\" >12500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow4_col4\" class=\"data row4 col4\" >30000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow4_col5\" class=\"data row4 col5\" >1830</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow4_col6\" class=\"data row4 col6\" >1.14%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow5_col0\" class=\"data row5 col0\" >computer</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow5_col1\" class=\"data row5 col1\" >13742</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow5_col2\" class=\"data row5 col2\" >3750</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow5_col3\" class=\"data row5 col3\" >12500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow5_col4\" class=\"data row5 col4\" >33750</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow5_col5\" class=\"data row5 col5\" >124213</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow5_col6\" class=\"data row5 col6\" >77.23%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow6_col0\" class=\"data row6 col0\" >realestate</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow6_col1\" class=\"data row6 col1\" >13106</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow6_col2\" class=\"data row6 col2\" >3750</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow6_col3\" class=\"data row6 col3\" >12500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow6_col4\" class=\"data row6 col4\" >30000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow6_col5\" class=\"data row6 col5\" >1918</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow6_col6\" class=\"data row6 col6\" >1.19%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow7_col0\" class=\"data row7 col0\" ></td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow7_col1\" class=\"data row7 col1\" >12929</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow7_col2\" class=\"data row7 col2\" >12500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow7_col3\" class=\"data row7 col3\" >12929</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow7_col4\" class=\"data row7 col4\" >14000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow7_col5\" class=\"data row7 col5\" >7</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow7_col6\" class=\"data row7 col6\" >0.00%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow8_col0\" class=\"data row8 col0\" >gov</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow8_col1\" class=\"data row8 col1\" >12854</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow8_col2\" class=\"data row8 col2\" >3750</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow8_col3\" class=\"data row8 col3\" >12000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow8_col4\" class=\"data row8 col4\" >29729</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow8_col5\" class=\"data row8 col5\" >1859</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow8_col6\" class=\"data row8 col6\" >1.16%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow9_col0\" class=\"data row9 col0\" >medical</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow9_col1\" class=\"data row9 col1\" >12751</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow9_col2\" class=\"data row9 col2\" >4500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow9_col3\" class=\"data row9 col3\" >11500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow9_col4\" class=\"data row9 col4\" >30000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow9_col5\" class=\"data row9 col5\" >3479</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow9_col6\" class=\"data row9 col6\" >2.16%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow10_col0\" class=\"data row10 col0\" >ads</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow10_col1\" class=\"data row10 col1\" >12395</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow10_col2\" class=\"data row10 col2\" >4000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow10_col3\" class=\"data row10 col3\" >11500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow10_col4\" class=\"data row10 col4\" >34000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow10_col5\" class=\"data row10 col5\" >1971</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow10_col6\" class=\"data row10 col6\" >1.23%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow11_col0\" class=\"data row11 col0\" >energy</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow11_col1\" class=\"data row11 col1\" >11944</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow11_col2\" class=\"data row11 col2\" >5000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow11_col3\" class=\"data row11 col3\" >11500</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow11_col4\" class=\"data row11 col4\" >25000</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow11_col5\" class=\"data row11 col5\" >1890</td> \n",
       "        <td id=\"T_a742ebae_69c3_11e9_9120_701ce71031efrow11_col6\" class=\"data row11 col6\" >1.18%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x233336f14e0>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_industry=get_sub_stats_by_col(data,'industry')\n",
    "apply_style(data_industry)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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